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StarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) have become integral in modern image rendering and graphic design applications due to their infinite …
Juan A. Rodriguez
,
Shubham Agarwal
,
Abhay Puri
,
Issam H. Laradji
,
Sai Rajeswar Mudumba
,
Pau Rodriguez
,
David Vazquez
,
Christopher Pal
,
Marco Pedersoli
ArXiv, 2024.
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TapeAgents: a Holistic Framework for Agent Development and Optimization
We present TapeAgents, an agent framework that leverages a structured, replayable log (tape) of the agent session to facilitate all …
Dzmitry Bahdanau
,
Nicolas Gontier
,
Gabriel Huang
,
Ehsan Kamalloo
,
Rafael Pardinas
,
Alexandre Piche
,
Torsten Scholak
,
Oleh Shliazhko
,
Jordan Prince Tremblay
,
Karam Ghanem
,
Soham Parikh
,
Mitul Tiwari
,
Quaizar Vohra
ArXiv, 2024.
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Video
Capture the Flag: Uncovering Data Insights with Large Language Models
The extraction of a small number of relevant insights from vast amounts of data is a crucial component of data-driven decision-making. …
Issam H. Laradji
,
Perouz Taslakian
,
Sai Rajeswar Mudumba
,
Valentina Zantedeschi
,
Alexandre Lacoste
,
Nicolas Chapados
,
David Vazquez
,
Christopher Pal
,
Alexandre Drouin
Workshop at the Neural Information Processing Systems (NeurIPS), 2023.
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The Unsolved Challenges of LLMs in Open-Ended Web Tasks: A Case Study
In this work, we investigate the challenges associated with developing goal-driven AI agents capable of performing open-ended tasks in …
Rim Assouel
,
Tom Marty
,
Massimo Caccia
,
Issam H. Laradji
,
Alexandre Drouin
,
Sai Rajeswar Mudumba
,
Hector Palacios
,
Quentin Cappart
,
David Vazquez
,
Nicolas Chapados
,
Maxime Gasse
,
Alexandre Lacoste
Workshop at the Neural Information Processing Systems (NeurIPS), 2023.
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CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
Handling out-of-distribution (OOD) samples has become a major stake in the real-world deploy- ment of machine learning systems. This …
Charles Guille-Escuret
,
Pau Rodriguez
,
David Vazquez
,
Ioannis Mitliagkas
,
João Monteiro
Conference on Neural Information Processing Systems (NeurIPS), 2023.
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Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Alexandre Lacoste
,
Sai Rajeswar Mudumba
International Conference of Learning Representations (ICLR), 2023.
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Haptics-based Curiosity for Sparse-reward Tasks
Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks …
Sai Rajeswar Mudumba
,
Cyril Ibrahim
,
Nitin Surya
,
Florian Golemo
,
David Vazquez
,
Aaron Courville
,
Pedro O. Pinheiro
Conference on Robot Learning (CoRL), 2022.
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A Planning based Neural-Symbolic Approach for Embodied Instruction Following
The ALFRED environment features an embodied agent following instructions and accomplishing tasks in simulated home environments. …
Xiaotian Liu
,
Hector Palacios
,
Christian Muise
Montreal AI Symposium (MAIS), 2022.
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Visual Question Answering From Another Perspective: CLEVR Mental Rotation Tests
Different types of mental rotation tests have been used extensively in psychology to understand human visual reasoning and perception. …
Christopher Beckham
,
Martin Weiss
,
Florian Golemo
,
Sina Honari
,
Derek Nowrouzezahrai
,
Christopher Pal
Pattern Recognition (PR), 2022.
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Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
As deep reinforcement learning driven by visual perception becomes more widely used there is a growing need to better understand and …
Christian Rupprecht
,
Cyril Ibrahim
,
Christopher Pal
International Conference on Learning Representations (ICLR), 2020.
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